Cloud task scheduling using nature inspired meta-heuristic algorithm

Syed Hasan Adil; Kamran Raza; Usman Ahmed; Syed Saad Azhar Ali; Manzoor Hashmani

doi:10.1109/ICOSST.2015.7396420

Cloud task scheduling using nature inspired meta-heuristic algorithm

Syed Hasan Adil, Kamran Raza, Usman Ahmed, Syed Saad Azhar Ali, Manzoor Hashmani

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Scopus citations

Abstract

In this paper we investigate the application of Meta-Heuristic for cloud task scheduling on Hadoop. Hadoop is an open source implementation of MapReduce framework which extensively used for processing computational intensive jobs on huge amount of data over multi-node cluster. In order to achieve an efficient execution schedule, the scheduling algorithm requires to determining the order and the node on which tasks will be executed. A scheduling algorithm uses execution time, order of task arrival and location of data (i.e., assign task to the node which contains the required data) to determine the best execution schedule. We use Particle Swarm Optimization (PSO) to determine the tasks execution schedule and compare with tasks schedules obtained from other techniques like Genetic Algorithm (GA), Brute Force (BF) algorithm, First In First Out (FIFO) algorithm and Delay Scheduling Policy (DSP) algorithm. The results of this study prove the significance of PSO algorithm for cloud task scheduling over other algorithms.

Original language	English
Title of host publication	ICOSST 2015 - 2015 International Conference on Open Source Systems and Technologies, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	158-164
Number of pages	7
ISBN (Electronic)	9781479978120
DOIs	https://doi.org/10.1109/ICOSST.2015.7396420
State	Published - 1 Feb 2016
Externally published	Yes
Event	9th International Conference on Open Source Systems and Technologies, ICOSST 2015 - Lahore, Pakistan Duration: 17 Dec 2015 → 19 Dec 2015

Publication series

Name	ICOSST 2015 - 2015 International Conference on Open Source Systems and Technologies, Proceedings

Conference

Conference	9th International Conference on Open Source Systems and Technologies, ICOSST 2015
Country/Territory	Pakistan
City	Lahore
Period	17/12/15 → 19/12/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

Brute Force Approach
Cloud Computing
Hadoop
MapReduce
Meta-Heuristic
Particle Swarm Optimization
Task Scheduling

ASJC Scopus subject areas

Software
Computer Science Applications
Signal Processing

Access to Document

10.1109/ICOSST.2015.7396420

Cite this

Adil, S. H., Raza, K., Ahmed, U., Ali, S. S. A., & Hashmani, M. (2016). Cloud task scheduling using nature inspired meta-heuristic algorithm. In ICOSST 2015 - 2015 International Conference on Open Source Systems and Technologies, Proceedings (pp. 158-164). Article 7396420 (ICOSST 2015 - 2015 International Conference on Open Source Systems and Technologies, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICOSST.2015.7396420

Adil, Syed Hasan ; Raza, Kamran ; Ahmed, Usman et al. / Cloud task scheduling using nature inspired meta-heuristic algorithm. ICOSST 2015 - 2015 International Conference on Open Source Systems and Technologies, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 158-164 (ICOSST 2015 - 2015 International Conference on Open Source Systems and Technologies, Proceedings).

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abstract = "In this paper we investigate the application of Meta-Heuristic for cloud task scheduling on Hadoop. Hadoop is an open source implementation of MapReduce framework which extensively used for processing computational intensive jobs on huge amount of data over multi-node cluster. In order to achieve an efficient execution schedule, the scheduling algorithm requires to determining the order and the node on which tasks will be executed. A scheduling algorithm uses execution time, order of task arrival and location of data (i.e., assign task to the node which contains the required data) to determine the best execution schedule. We use Particle Swarm Optimization (PSO) to determine the tasks execution schedule and compare with tasks schedules obtained from other techniques like Genetic Algorithm (GA), Brute Force (BF) algorithm, First In First Out (FIFO) algorithm and Delay Scheduling Policy (DSP) algorithm. The results of this study prove the significance of PSO algorithm for cloud task scheduling over other algorithms.",

keywords = "Brute Force Approach, Cloud Computing, Hadoop, MapReduce, Meta-Heuristic, Particle Swarm Optimization, Task Scheduling",

author = "Adil, \{Syed Hasan\} and Kamran Raza and Usman Ahmed and Ali, \{Syed Saad Azhar\} and Manzoor Hashmani",

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doi = "10.1109/ICOSST.2015.7396420",

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Adil, SH, Raza, K, Ahmed, U, Ali, SSA & Hashmani, M 2016, Cloud task scheduling using nature inspired meta-heuristic algorithm. in ICOSST 2015 - 2015 International Conference on Open Source Systems and Technologies, Proceedings., 7396420, ICOSST 2015 - 2015 International Conference on Open Source Systems and Technologies, Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 158-164, 9th International Conference on Open Source Systems and Technologies, ICOSST 2015, Lahore, Pakistan, 17/12/15. https://doi.org/10.1109/ICOSST.2015.7396420

Cloud task scheduling using nature inspired meta-heuristic algorithm. / Adil, Syed Hasan; Raza, Kamran; Ahmed, Usman et al.
ICOSST 2015 - 2015 International Conference on Open Source Systems and Technologies, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. p. 158-164 7396420 (ICOSST 2015 - 2015 International Conference on Open Source Systems and Technologies, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - In this paper we investigate the application of Meta-Heuristic for cloud task scheduling on Hadoop. Hadoop is an open source implementation of MapReduce framework which extensively used for processing computational intensive jobs on huge amount of data over multi-node cluster. In order to achieve an efficient execution schedule, the scheduling algorithm requires to determining the order and the node on which tasks will be executed. A scheduling algorithm uses execution time, order of task arrival and location of data (i.e., assign task to the node which contains the required data) to determine the best execution schedule. We use Particle Swarm Optimization (PSO) to determine the tasks execution schedule and compare with tasks schedules obtained from other techniques like Genetic Algorithm (GA), Brute Force (BF) algorithm, First In First Out (FIFO) algorithm and Delay Scheduling Policy (DSP) algorithm. The results of this study prove the significance of PSO algorithm for cloud task scheduling over other algorithms.

AB - In this paper we investigate the application of Meta-Heuristic for cloud task scheduling on Hadoop. Hadoop is an open source implementation of MapReduce framework which extensively used for processing computational intensive jobs on huge amount of data over multi-node cluster. In order to achieve an efficient execution schedule, the scheduling algorithm requires to determining the order and the node on which tasks will be executed. A scheduling algorithm uses execution time, order of task arrival and location of data (i.e., assign task to the node which contains the required data) to determine the best execution schedule. We use Particle Swarm Optimization (PSO) to determine the tasks execution schedule and compare with tasks schedules obtained from other techniques like Genetic Algorithm (GA), Brute Force (BF) algorithm, First In First Out (FIFO) algorithm and Delay Scheduling Policy (DSP) algorithm. The results of this study prove the significance of PSO algorithm for cloud task scheduling over other algorithms.

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Y2 - 17 December 2015 through 19 December 2015

ER -

Adil SH, Raza K, Ahmed U, Ali SSA, Hashmani M. Cloud task scheduling using nature inspired meta-heuristic algorithm. In ICOSST 2015 - 2015 International Conference on Open Source Systems and Technologies, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. p. 158-164. 7396420. (ICOSST 2015 - 2015 International Conference on Open Source Systems and Technologies, Proceedings). doi: 10.1109/ICOSST.2015.7396420

Cloud task scheduling using nature inspired meta-heuristic algorithm

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this